Chief Data Strategist
6 days ago
Aegistech Seeks Expert Lead Data Scientist
As a key member of our Data Science & Analytics team, you will play a crucial role in pushing the boundaries of our analytics and predictive capabilities. With a strong focus on research, experimentation, and data modeling techniques, you will work closely with our team to develop and implement advanced & predictive analytics solutions that drive business growth and margin.
Key Responsibilities:
- Exposing Insights: Turn data into actionable information by producing analysis reports and diagnostic models to uncover hidden relationships and patterns between our data and key metrics.
- Evaluate & Produce Quality: Ensure high-quality code by reviewing your own and your teammates' code, ensuring it is free from errors, bias, and easy to understand.
- Data Engineering: Gather, clean, and preprocess data from various sources, performing feature engineering to improve dataset quality and usefulness. Deploy pipelines on cloud-based infrastructure.
- Predictive Modeling: Develop, validate, and deploy predictive models using machine learning algorithms and statistical techniques, such as regression, classification, clustering, time series forecasting, and optimization.
- Generative Modeling: Utilize open-source and paid technologies to produce abstractions and novel features for other applications.
- Continuous Improvement: Stay up-to-date with the latest developments in data science, machine learning, and reporting technologies, contributing to knowledge-sharing sessions to grow and develop others.
- 6+ years of experience in data science or machine learning roles.
- Familiarity with business efficiency metrics, including Customer Acquisition Cost (CAC), Revenue Acquisition Cost (RAC), Retention, Margin, Annual Recurring Revenue (ARR), Lifetime Value (LTV), and Engagement.
- Experience with at least one dashboarding tool, such as Tableau, Power BI, Looker, Google Data Studio, Streamlit, Dash, etc.
- Proficiency with Python and SQL.
- Knowledge of machine learning algorithms and statistical techniques for predictive modeling, including Regression, Classification, Clustering, Time Series Analysis, and Optimization.
- Proficiency with end-to-end pipelines.
- Expert knowledge in model evaluation metrics.
- Experience pulling data from various third-party systems and APIs.
- Proficiency with version control.
- Proven ability to work both independently and as part of a team.
- Proficiency with visualization in Python.
- Familiarity with best practices in secure data handling and customer data privacy.
- $120,000 - $180,000 annual salary depending on location and experience.
- Flexible PTO.
- All benefits: medical, dental, and vision insurance, 401(k) with employer match, short- and long-term disability coverage, life insurance options, and paid parental leave.
- Certification reimbursement program.
- Work from anywhere in the US.
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